Core Viewpoint - Alice Agent is an innovative tool designed to enhance efficiency and personalization in the financial industry, addressing common pain points faced by users of similar products [1][2]. Summary by Sections User Growth and Adoption - Since its launch, Alice Agent has experienced exponential user growth, with daily trial users surpassing historical records and functionality usage reaching new peaks [1]. Problem Solving - Alice Agent effectively resolves issues prevalent in other agent products, such as unstable task planning, unreliable data sources, and significant AI hallucinations. It leverages Wind's financial big data platform for dynamic task planning and real-time coding technology, ensuring stable and accurate task execution [1][2]. Functionality and Features - The platform allows users to automate complex tasks, such as market analysis, by simply inputting objectives. For example, users can request a report on recent market trends, and Alice Agent will generate a comprehensive analysis, including data collection, news filtering, and result analysis, all in one step [2][3]. - Outputs can be generated in various formats, including Word, Excel, and PDF, and can incorporate visual tools like charts and mind maps, enhancing clarity and collaboration within teams [2]. Task Execution Process - The task execution process includes: 1. Gathering recent hot topic news 2. Collecting relevant research reports 3. Analyzing industry and concept sector performance 4. Generating visual data representations 5. Assessing the sustainability of hot topics 6. Compiling findings into a Word report and emailing it [3]. Market Insights - The article highlights recent market trends, including sector performance, with notable increases in areas such as: - Communication: +5.27% - Non-ferrous metals: +3.74% - Electronics: +3.60% - Gene editing: +15.88% - Charging stations: +11.86% [4]. Conclusion - Alice Agent represents a significant advancement in financial tools, promoting a future of "easy and efficient" work for financial professionals, including researchers, fund managers, and investment advisors [4][6].

Core Viewpoint - Bloomberg has launched a real-time event data solution that provides a unified data channel for market events, news insights, market data, pricing, and analysis, enhancing its B-PIPE market data transmission product [1][2]. Group 1: Real-time Event Data Solution - The solution extracts and standardizes data from unstructured sources in real-time, addressing the challenges faced by front-office professionals in managing dispersed information and monitoring thousands of securities [1][2]. - It allows clients to receive real-time updates through a subscription mechanism, enabling them to focus on relevant event dynamics rather than passively receiving large amounts of information [1][2]. Group 2: Automation and Quality Control - Bloomberg combines automated processes with analyst oversight to provide critical event data streams that meet the speed and consistency demands of front-office teams [2]. - The solution employs automated data collection, text analysis, and data parsing technologies to capture hundreds of thousands of announcements and news releases at the moment of publication, with quality control measures enhancing data accuracy [2]. Group 3: Product Offerings - The real-time event data solution includes several products: - Company Earnings Data Stream, covering over 10,000 companies and key performance indicators (KPIs) [2]. - Company Event Calendar, providing forward-looking schedules and updates for over 50,000 listed companies [2]. - Economic Bulletin Data Stream, offering comprehensive data on over 3,000 market-impacting indicators from more than 100 countries [2]. Group 4: Access and Integration - Users can access company earnings data through {MODL <GO>}, company event calendar data through {EVTS <GO>}, and economic bulletin data through {ECO <GO>} [3]. - The solution is designed for flexible use across various internal departments and integrates with Bloomberg Terminal desktop solutions to ensure data consistency between user operations and automated workflows [2].

Core Insights - The company has launched a retail credit data visualization service to enhance data readability and value extraction [1][2] - The initiative aims to overcome the challenges of data fragmentation and low timeliness, enabling business personnel to access effective data quickly [1] - The service utilizes advanced technologies such as stream computing and dynamic visualization to provide real-time data support for business decision-making [1] Group 1: Data Integration and Efficiency - Prior to the new service, data development required traditional methods involving lengthy delivery cycles by R&D personnel [2] - The new drag-and-drop self-service feature allows business personnel to directly engage with data, significantly improving efficiency and automation [2] - The service has built nearly a thousand dimensional indicators and achieved nearly 200,000 access visits, with mobile engagement leading among departments [2] Group 2: Future Development - The company plans to continue optimizing the retail credit data visualization service in collaboration with its data management department [2] - The focus will be on enhancing the user experience and providing more efficient and agile services in the retail credit business domain [2]

Core Insights - FactSet is actively investing in Gen AI solutions, leveraging its extensive database and flexible analytical tools to provide a range of Gen AI offerings [1] - The upcoming seminar will focus on the latest applications of Gen AI in the financial sector and share real-world case studies from overseas financial institutions [3] Group 1: Seminar Details - The seminar titled "Gen AI in Financial Industry: Insights from Overseas Cases" is scheduled for June 19, 2025, from 15:00 to 17:00, followed by a cocktail reception [3] - The event will take place at the Shangri-La Hotel in Pudong, Shanghai, with registration available via a QR code [3] Group 2: Agenda Highlights - The opening session will introduce how FactSet's Gen AI solutions can drive business innovation, focusing on enhancing work efficiency and automating processes [5] - A segment will present real-world applications of Gen AI by overseas clients, providing innovative references for domestic financial professionals [6] - The final part will discuss the challenges of rising costs in data management and how FactSet's DaaS solutions can facilitate efficient data collection and access [7] Group 3: Speaker Information - Patrick Starling, Senior Vice President and Senior Director of Product Management at FactSet, will lead discussions on the generative AI data platform and related services [11]

Group 1 - The core focus of the article is on the application of Gen AI solutions in the financial sector, highlighting the latest trends and real-world case studies from overseas financial institutions [1][6][7] - A seminar is scheduled to discuss the innovative use of Gen AI in business operations, emphasizing efficiency improvements and automation through FactSet's solutions [6][8] - The event will feature a cocktail session, providing networking opportunities for participants [5][9] Group 2 - The seminar will include presentations on how Gen AI can drive business innovation and enhance analytical accuracy, with discussions on the new value it brings to users [6][7] - Real-life examples of Gen AI applications from overseas clients will be shared, offering insights for domestic financial professionals on potential innovative strategies [7] - The challenges of rising costs in data management and processing for Gen AI strategies will be addressed, along with FactSet's DaaS solutions to streamline access to critical financial data [8]

15分钟彭博企业数据入门 网络研讨会 数据等各类数据于一处，为企业前、中、后台的用户提供一个通用、同频且值得信赖的参考框 2025年5月27日（星期二）| 上午10:00 "对齐颗粒度"可谓当今企业在数据应用方面的一大挑战：当重要数据分散于不同系统和模块，将 其进行对齐、整理、分析的难度日益增加。企业亟需能将数据获取一体化、贯通前中后台的解决 方案。彭博企业数据服务（Enterprise Data）集参考数据、监管数据、定价数据、ESG数据、另类 据服务如何为贵企业的工作流程带来助力！ 主讲内容： 彭博静态数据集产品(Data License)为企业整体提供彭博数据集，包括参考数据，定价数据和监管数据，为 财务、投资组合管理与合规系统提供超过5,000万条证券和超过15,000个字段信息。 Data License助您以企业级访问获取终端海量数据集 DATA 功能演示：快速找到彭博数据，一键访问并应用 * 报名需要时间审核，敬请耐心等待。审核通过将在微信收到报名成功提醒，活动开始前将会收到具体参会提醒，请注意查收！ * 彭博Bloomberg保留活动的最终解释权。 Data Dynamics： 彭博推出全新的 ...

"随着全球交易员在国际固定收益市场中评估投资机遇，以求解锁超额收益并优化交易执行，对 实时定价洞察的需求也在日益增长，以提升交易工作流程的透明度。此次扩展将IBVAL的高质 量、AI驱动的定价洞察扩大到部分最具流动性的国际债券市场，令跨时区的买卖双方交易员在 做出交易决策和收获交易成果时更具信心。" 新兴市场债券的纳入标志着IBVAL定价数据的最新扩展。IBVAL于2023年 推出 ，最初涵盖美元 信用证券定价，次年拓展至所有欧元和英镑的投资级和高收益信用债。IBVAL依托为处理数十亿 条跳价的复杂市场数据而设计的机器学习模型，以每15秒一次的更新速度提供各种流动性等级债 券的高质量定价信息。 您可以通过在彭博终端上加载证券，然后选择IBVL PCS作为首选定价来源，获取IBVAL数据。客 户也可以通过彭博的实时市场数据传输（B-PIPE）访问IBVAL数据，轻松整合企业内部的各项日 内定价数据。如需了解更多信息，请在彭博终端访问{IBVL}。 点击 " 阅读原文 " ，进一步了解彭博前台日内定价数据（IBVAL）。 纳入新兴市场债券，可以让买卖双方交易员将自动定价无缝整合到其交易工作流程中，拓展更多新 兴市 ...

Core Viewpoint - The article discusses the innovative approach of using large language models (LLMs) to analyze earnings call transcripts, enabling analysts to assess the sentiment of CEOs regarding future business outlooks and their potential impact on stock prices [1][2]. Group 1: Advanced Earnings Call Analysis - LSEG MarketPsych Transcript Analytics integrates LSEG's data resources with MarketPsych's natural language processing (NLP) capabilities, providing sentiment analysis and thematic data for over 16,000 publicly listed companies [2][3]. - The solution identifies over 1,000 themes and 4,000 event types within earnings call transcripts, allowing for detailed sentiment classification and analysis [3][4]. Group 2: Application Scenarios - Companies with high sentiment scores in earnings calls tend to outperform those with lower scores in the following month, indicating a correlation between CEO sentiment and stock performance [6]. - The built-in ESG sentiment classifier can dynamically monitor ESG-related sentiments, providing risk warnings for companies with low ESG sentiment scores [6][7]. - The analysis system can also quantify the frequency and sentiment of key negative terms mentioned by executives, aiding in risk management and credit risk monitoring [7].

自2023年起，在"国九条"的指导下，中国国务院发布了《关于加强监管防范风险推动资本市场高质量发展 的若干意见》。继中国证监会（CSRC）相关公告发布之后，一系列有关股利支付政策的指导文件也相继出 台。 2024年4月，上海、深圳和北京证券交易所分别对其上市规则进行了修改，包括股利发放以及风险预警机 制。上市公司必须建立健全的利润分配体系，积极回馈股东。一旦股利支付低于一定门槛则可能面临风险 警示，暨被标记为"特别处理"（ST股）。 本文将具体讨论证交所发布的政策对A股市场的意义，并介绍 彭博终端股利预测 （BDVD）功能 如何凭借 定性分析、基本面分析及趋势和模型分析，回测股利支付日期，识别股利发放趋势，最终赋能买方及卖方 的投资交易决策。 股利支付政策综述 交易所将根据以下三个因素审查上市公司的历史股利金额：1）哪些公司必须支付，2）必须支 付的金额，3）是否存在例外情况。 1. 最近三个财政年度的累计研发投资占其累计收入的15%以上 2. 最近三个财政年度的累计研发投资超过3亿元人民币 BDVD显示彭博分析师对特定股票、股指、ETF或投资组合所做出的股利预测。该界面可帮助 您深入了解未来现金流，并更好地 ...

绿色经济由提供具有环境效益产品和服务的企业构成——涵盖从可再生能源和清洁水源到节能建筑和回收服 务的各个领域。这些解决方案贯穿整个价值链，对于应对气候变化以及更广泛的环境挑战至关重要。 在全球不确定性加剧的背景下，本研究分析了绿色经济的波动与长期增长驱动力。 识别绿色价值需要可靠的数据和精准的洞察。自2008年以来，LSEG一直致力于开发专有数 据、分析工具及指数，以衡量企业在绿色经济领域的敞口。本报告展示了这些解决方案的实际 当前，绿色经济领域正面临市场波动，我们发布的《2025年绿色经济投资》报告，旨在帮助投资者剖析短 期市场波动，并挖掘绿色经济的长期增长驱动力及潜在投资机遇。 阅读我们的第六份 年度《投资绿色经济》报告 长按上方二维码 查看我们的报告（英文版） 为何这项研究为何这项研究如此重要？ 获取关于绿色经济全球 增长轨迹和表现的数据驱动型洞察 了解塑造绿色投资机遇的关键地域和行业趋势 探索由气候变化适应所带来的 投资机遇 应用。 在分析过程中，我们运用了LSEG多种专有的可持续发展投资数据，其中涵盖 绿色收入数据 、 气候数据 、 固定收益数据 、 Lipper基金的资金流动与持仓数据 、 大宗商 ...